A proposal is made for the design and testing of a new system for computer aided medical diagnosis. The model will be designed with the intention of approaching solutions to two specific problems that have limited the effectiveness and practicality of previous computer based models: 1) how to account for the existance of multiple diagnoses; 2) how to recognize and represent conditional dependencies among data. The model will be developed and tested in the context of a specific problem area: the differential diagnosis of chest pain. The study will make use of a large data base that has already been collected on the clinical problem of chest pain. The medical knowledge in the model will be derived from two expert panels of physicians who will have access to the statistical data from one part of the data base (the "model building cases"). Then the performance of the model will be tested on the other part of the data base (the "model validation cases") and its performance will be compared with the performance of three other models, a standard Bayesian model, a linear discriminant model, and a logistic model.